The microstructure of Ti6Al4V alloy, manufactured using laser powder bed fusion (L-PBF), is affected by process parameters and heat treatment. However, their influence on the nano-mechanical behavior of this widely applicable alloy is still unknown and scarcely reported. This study aims to investigate the influence of the frequently used annealing heat treatment on mechanical properties, strain-rate sensitivity, and creep behavior of L-PBF Ti6Al4V alloy. Furthermore, the influence of different utilized L-PBF laser power–scanning speed combinations on mechanical properties of annealed specimens has been studied as well. It has been found that the effect of high laser power remains present in the microstructure even after annealing, resulting in increase in nano-hardness. Moreover, the linear relation between the Young’s modulus and the nano-hardness after annealing has been established. Thorough creep analysis revealed dislocation motion as a dominant deformation mechanism, both for as-built and annealed conditions of the specimens. Although annealing heat treatment is beneficial and widely recommended, it reduces the creep resistance of Ti6Al4V alloy manufactured using L-PBF. The results presented within this research article contribute to the L-PBF process parameter selection, as well as to understanding the creep behavior of these novel and widely applicable materials.

The mechanical behavior of the metallic components fabricated by additive manufacturing (AM) technologies can be influenced by adjustments in their microstructure or by using specially engineered geometries. Manipulating the topological features of the component, such as incorporating unit cells, enables the production of lighter metamaterials, such as lattice structures. This study investigates the mechanical behavior of lattice structures created from AlSi10Mg, which were produced using the laser beam powder bed fusion (LB-PBF) process. Specifically, their behavior under pure compressive loading has been numerically and experimentally investigated using ten different configurations. Experimental methods and finite element analysis (FEA) were used to investigate the behavior of body-centered cubic (BCC) lattice structures, specifically examining the effects of tapering the struts by varying their diameters at the endpoints ($d_{\mathrm{end}}$) and midpoints ($d_{\mathrm{mid}}$), as well as altering the height of the joint nodes (h). The unit cells were designed with varying parameters in such a way that $d_{\mathrm{end}}$ is changed at three levels, while $d_{\mathrm{mid}}$ and h are changed at two levels. Significant differences in Young’s modulus, yield strength, and ultimate compressive strength between the various specimen configurations were observed both experimentally and numerically. The FEA underestimated the Young’s modulus corresponding to the configurations with thinner struts in comparison to the higher values found experimentally. Conversely, the FEA overestimated the Young’s modulus of those configurations with larger strut diameters with respect to the experimentally determined values. Additionally, the proposed FE method consistently underestimated the yield strength relative to the experimental values, with notable discrepancies in specific configurations.

This study addresses the lack of comprehensive understanding regarding how both structural printing parameters and environmental factors influence the mechanical properties of additively manufactured polymer and composite materials. The main problem stems from insufficient data on the combined effects of infill density, number of perimeters, layer height, and exposure to cooling lubricants on the tensile performance of 3D-printed products, which is crucial for their reliable application in demanding environments. In this research, the influence of four critical parameters—infill density, number of perimeters, layer height, and exposure to cooling lubricants—on the tensile properties of specimens produced by fused filament fabrication (FFF), also known as fused deposition modeling (FDM), from polylactic acid (PLA) and polylactic acid reinforced with carbon fibers (PLA+CF) was investigated. Tensile tests were performed in accordance with ISO 527-2 on specimens printed with honeycomb infill structures under controlled process conditions. The results show that increasing infill density from 40% to 100% led to an approximately 60% increase in tensile strength for both PLA (from 30.75 MPa to 49.11 MPa) and PLA reinforced with carbon fibers (PLA+CF; from 17.75 MPa to 28.72 MPa). Similarly, increasing the number of perimeters from 1 to 3 resulted in a 51% improvement in tensile strength for PLA and 50% for PLA+CF. Reducing layer height from 0.40 mm to 0.20 mm improved tensile strength by 5.4% for PLA and 3.1% for PLA+CF, with more pronounced gains in stiffness observed in the composite material. Exposure to cooling lubricants led to mechanical degradation: after 30 days, PLA exhibited a 15.2% decrease in tensile strength and a 3.4% reduction in Young’s modulus, while PLA+CF showed an 18.6% decrease in strength and a 19.5% drop in modulus. These findings underscore the significant impact of both structural printing parameters and environmental exposure on tailoring the mechanical properties of FFF-printed materials, particularly when comparing unfilled PLA with carbon fiber-reinforced PLA.

Controlling the surface roughness of materials manufactured by laser powder bed fusion (L-PBF) is critical for achieving functional performance of components and improving their mechanical properties. This is important for components whose surfaces cannot be post-treated using subtractive methods. In this study, the surface roughness has been investigated by applying different laser power and scanning speed combinations. Furthermore, potential effects of different locations on the build platform have been considered as well. The regression models have been developed using significant predictor variables, with their levels defined using face-centered central composite design. The analysis of variance (ANOVA) procedure has been used to evaluate the statistical significance of factors and model performances for each prediction variable. It has been found that the average surface roughness of L-PBF Ti6Al4V alloy can be described with high fitting accuracy using laser power and scanning speed as predictor variables. The position of specimens on the build platform showed no statistically significant effect on the average surface roughness. The experimental research and statistical analysis reported in this paper will contribute to a better understanding of how position, laser power, and scanning speed influence the average surface roughness of L-PBF Ti6Al4V alloy.

Soft pneumatic glove actuators for hand rehabilitation require compact, accurate models that can be evaluated in real time. At the same time, high-fidelity finite element (FE) simulations are too slow for iterative design and control. We develop a finite element-based calibration pipeline that combines a dependency-constrained human finger kinematic model with a segmented pseudo-rigid-body (PRB) description of ribbed-bellow soft pneumatic actuators sized to individual fingers. FE models with symmetry and contact generate pressure–pose data for the MCP, PIP, and DIP spans, from which we extract per-segment bending angles and axial elongations, fit simple pressure–kinematics relations, and identify PRB parameters using basin-hopping global optimization. The calibrated PRB reproduces FE flexion–extension trajectories for index and little finger actuators with millimetric accuracy (mean segment positioning errors of approximately 2.3 mm and 0.7 mm), preserves finger-like bending localized in the bellows, and maintains negligible compression of inter-joint links (below 1.2%). The pressure–bend and pressure–elongation maps achieve near-unity adjusted $R^2$, and the PRB forward kinematics evaluates complete pressure trajectories in less than half a millisecond, compared with several hours for the corresponding FE simulations. This pipeline provides a practical route from detailed FE models to controller-ready reduced-order surrogates for design-space exploration and patient-specific control of soft rehabilitation actuators.